基于多域网络的红外目标跟踪算法

随着红外探测器性能的不断提升, 红外目标跟踪在智能安防等领域的应用越来越广泛。然而红外图像分辨率较低, 依赖其进行目标跟踪仍然是一个制约相关应用发展的难题。针对红外图像分辨率低的特点, 以多域网络为模型算法框架, 结合目标运动过程中的尺寸变化特点, 提出了一种基于多域网络的红外目标跟踪算法。为了评估算法性能, 分别在VOT-TIR2016数据库和AMCOM红外数据上进行了实验。实验结果表明, 目标尺度预测机制能够显著提高算法的跟踪精度。     

彩色多普勒超声诊断腹腔干动脉狭窄的临床价值

目的探讨彩色多普勒超声检查在评估腹腔干动脉狭窄中的价值。方法应用彩色多普勒超声诊断仪对腹痛患者的腹腔干动脉进行检查,观察的内容包括腹腔干起始段管腔有无斑块、血栓等引起的狭窄,测量腹腔干狭窄处收缩期峰值速度(peak systolic velocity,PSV)。以30例门诊常规体检患者为对照组,彩色多普勒检查对照组腹腔干二维声像改变,并测量起始段血流PSV。结果彩色多普勒超声共检出24例腹腔干动脉狭窄,其中起始段粥样硬化斑块16例,血栓栓塞7例,孤立性夹层动脉瘤并血栓形成1例。狭窄处血流PSV最高为420 cm/s,最低为228 cm/s,平均为(304.52±53.75)cm/s。对照组腹腔干起始段血流PSV最高为178 cm/s,最低为81 cm/s,平均为(113.33±19.70)cm/s。狭窄组患者腹腔干狭窄处血流速度明显高于对照组起始段血流速度,差异有统计学意义(t=16.242,P<0.000 1)。结论彩色多普勒超声检查对腹腔干狭窄诊断价值较高,能够准确显示腹腔干狭窄的部位、狭窄程度和血流动力学的改变,对腹痛患者的病因筛选有重要的临床意义。     

毫米波合成孔径成像辐射计

合成孔径辐射计应用于空间被动遥感,成功地解决了机载大尺寸天线的制作安装困难。本文首次提出把毫米波技术与合成孔径辐射计技术相结合应用于武器制导系统,并在介绍干涉法合成孔径技术的基础上给出了一套毫米波合成孔径辐射计成像系统的方案。同时对图像重建算法做了深入探讨。     

一种补偿因子区域不变的CS成像算法

为提高星载合成孔径雷达（SAR）成像的实时性,减小补偿因子的运算量,提出了一种补偿因子区域不变的Chirp Scaling（CS）成像算法. 这种改进的CS算法根据补偿因子的相位误差确定一个更新步长,在每个步长内更新一次补偿因子,即相邻单元内的数据与相同的补偿因子相乘. 利用这种改进的CS算法对点阵目标和实测目标进行了仿真验证,得到的SAR图像质量与传统CS算法的结果相差很小. 这种补偿因子区域不变的CS成像算法在满足精度的前提下使得补偿因子的运算量成倍减小,大大减小了实时成像的压力,能够有效降低星上实时处理系统的规模,从而降低系统功耗.      

Factors affecting the voxel-based analysis of diffusion tensor imaging

Diffusion tensor imaging （DTI） provides a unique method to reveal the integrity of white matter microstructure noninvasively. Voxel-based analysis （VBA）, which is a highly reproducible and user-independent tech- nique, has been used to analyze DTI data in a number of studies. Fractional anisotropy （FA）, which is derived from DTI, is the most frequently used parameter. The parameter setting during the DTI data preprocessing might affect the FA analysis results. However, there is no reliable evidence on how the parameters affect the results of FA analysis. This study sought to quantitatively investigate the factors that might affect the voxel-based analysis of FA; these include the interpolation during spatial normalization, smoothing kernel and statistical threshold. Because it is difficult to obtain the true information of the lesion in the patients, we simulated lesions on the healthy FA maps. The DTI data were obtained from 20 healthy subjects. The FA maps were calculated using DTIStudio. We randomly divided these FA maps into two groups. One was used as a model patient group, and the other was used as a normal control group. Simulated lesions were added to the model patient group by decreasing the FA intensities in a specified region by 5 %- 50 %. The model patient group and the normal control groupwere compared by two-sample t test statistic analysis voxel- by-voxel to detect the simulated lesions. We evaluated these factors by comparing the difference between the detected lesion through VBA and the simulated lesion. The result showed that the space normalization of FA image should use the trilinear interpolation, and the smoothing kernel should be 2-3 times the voxel size of spatially normalized FA image. For lesions with small intensity change, FWE correction must be cautiously used. This study provided an important reference to the analysis of FA with VBA method.     

Big data analysis of the human brain’s functional interactions based on fMRI

The human brain is a huge, complex system generating brain activity. The exploration of human brain function using functional magnetic resonance imaging （fMRI） is a promising method to understand brain activity. However, the complexity of the big data generated by fMRI facilitates the analysis of various levels of human brain activity, such as the distribution of neural represen- tations, the interaction between different regions, and the dynamic interaction over time. These different levels can depict distinct prospects of the human brain activity, and considerable progress has been achieved. In the future, more big data analysis methods combining advances in computer science, including larger-scale computing, machine learning, and graph theory, will promote the understanding of the human brain.     

Assessment of alternated cooling and heating treatment by US combined CEUS in the VX2 rabbit liver tumor model

Inoperable liver tumors are often treated by thermal ablation that destroys the tumor in situ and spares the adjacent hepatic tissue.Thermal–physical treatment has many advantages,but treatment by freezing or heating alone has some limitations.By taking the advantages and disadvantages of cryosurgery and thermotherapy into consideration,a new thermal technique that combines cryosurgery and radio frequency ablation has been proposed,thereby overcoming the disadvantages of each treatment strategy and improving therapeutic outcomes.This new approach remains to be systematically studied in the liver;therefore,this study was performed to estimate survival after alternated cooling and heating ablation therapy in a VX2 rabbit liver tumor model.Sixteen days after VX2 carcinoma implantation into the rabbit liver,tumors were treated with alternated cooling and heating ablation therapy.Rabbits were monitored for 6 months after treatment and assessed with ultrasound(US)and computed tomography at 1,7,14,and 30 days posttreatment.Untreated tumor-bearing animals served as the control group.Our results show that alternate freezing and heating ablation therapy resulted in a good recovery of VX2 rabbits.Compared with the control group,treated rabbits lived significantly longer(P\0.05),with 70%of treated animals surviving to 196 days posttreatment without metastasis or recurrence,while none of the controls did so.There was no local recurrence in the treatment group.All rabbits in the control group developed metastasis,while metastasis was only observed in 30% of treated rabbits.These results suggest that alternate cooling and heating ablation therapy can prolong the survival time of rabbits with VX2 liver tumors and is an effective method for tumor therapy.Furthermore,we also showed in this model that contrast enhanced US is a valid follow-up approach to assess treatment effectiveness.     

时域光学拓扑成像方法的模拟和实验研究

针对现有的以修正的朗伯-比尔定律(modified Lambert-Beer law,MLBL)为理论模型的光学拓扑方法存在量化度不准确的问题,提出了一种基于最小二乘拟合算法的时域光学拓扑成像方法.该方法利用时域扩散方程在半无限空间条件下的解析解和测量曲线实现最佳匹配以计算相邻的源点与探测点之间的待测组织吸收系数变化值.对该时域光学拓扑成像方法进行了一系列的模拟验证,并以基于时间相关单光子计数(time-correlated single photon counting,TCSPC)技术的多通道时间分辨测量系统为平台进行了实验验证.结果表明:所提出的最小二乘拟合算法总体上优于传统的基于经验值光程的MLBL方法.     

利用复合型介质透镜的毫米波成像研究

毫米波焦平面成像技术有广泛的应用前景.本文采用一种复合型介质透镜,将其用于主动式毫米波成像系统,测量了透镜材料的折射率,对金属板进行成像,得到了轮廓较为清晰的图像.     

基于xy非线性梯度场磁共振成像研究

为解决非线性梯度成像中心分辨率低的问题,提出了一种基于xy非线性梯度场的成像方法,并讨论了非线性梯度场中心分布曲线对磁共振图像的影响. 研究结果表明,在半径r=1.5时,圆形中心分布曲线的图像重建结果最优;与O-Space技术对比实验表明,xy非线性梯度场在不同加速因子R下都得到了更好的重建结果.